發(fā)布時間：2018-11-23 18:33

【摘要】：肝硬化的計算機輔助診斷對肝臟疾病的早期治療和診斷具有重要意義。針對B超圖像中肝硬化病變區(qū)域邊緣模糊和回聲不均勻、尺度因素影響等問題,提出了改進的LBP算法并提取了相應(yīng)的SLBP特征。該特征較傳統(tǒng)的紋理特征更準(zhǔn)確地描述了B超圖像中肝硬化病變的特征,結(jié)合二維Gabor變換,解決了上述難題。鑒于傳統(tǒng)的機器學(xué)習(xí)方法的訓(xùn)練時間較長,采用基于超限學(xué)習(xí)機的訓(xùn)練方法,并首次將其應(yīng)用于肝硬化識別。實驗結(jié)果表明,所提方法對測試集的分類準(zhǔn)確率達到95.4%,在時間效率上較傳統(tǒng)方法有很大提高。ROC曲線表明,提出的分類方法在準(zhǔn)確率和泛化能力上均優(yōu)于傳統(tǒng)方法,有助于肝硬化的臨床診斷。
[Abstract]:Computer aided diagnosis of liver cirrhosis is of great significance for early treatment and diagnosis of liver diseases. An improved LBP algorithm is proposed and the corresponding SLBP features are extracted in order to solve the problems of edge blur and non-uniformity of echo and the influence of scale factors in B-mode ultrasound images. This feature is more accurate than the traditional texture features in describing the liver cirrhosis in B-mode ultrasound images. The above problems are solved by combining two-dimensional Gabor transform. In view of the long training time of the traditional machine learning method, the training method based on the transcendental learning machine is adopted, and it is applied to the liver cirrhosis recognition for the first time. The experimental results show that the classification accuracy of the proposed method is 95.4, and the time efficiency of the proposed method is much higher than that of the traditional method. The ROC curve shows that the proposed classification method is superior to the traditional method in accuracy and generalization ability. It is helpful for the clinical diagnosis of liver cirrhosis.
【作者單位】： 青島大學(xué)計算機科學(xué)技術(shù)學(xué)院;山東省數(shù)字醫(yī)學(xué)與計算機輔助手術(shù)重點實驗室;加州大學(xué)洛杉磯分校;
【基金】：國家自然科學(xué)基金項目:計算機輔助肝纖維化無創(chuàng)診斷(61303079);國家自然科學(xué)基金項目:空變運動模糊圖像的盲復(fù)原變分模型及其快速算法(61305045)資助
【分類號】：R575.2;TP391.41

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